SAP SE
Learning graph-based priors for generalized zero-shot learning

Abstract:

An image is received for classification. Thereafter, features are extracted from the image which are used by a machine learning model to classify the image. Thereafter, data is provided that characterizes the classification. The machine learning model can be trained using a training data set labeled, in part, using a generative model conditioned on label attribute information in combination with a directed relation graph having a plurality of nodes in which each node without images at training time are given predefined probability distributions. Related apparatus, systems, techniques and articles are also described.